Although there are currently a wide variety of software packages
suitable for the modern statistician, R has the triple advantage of
being comprehensive, widespread, and free. Published in 2008, the
second edition of Statistiques avec R enjoyed great success as an R
guidebook in the French-speaking world. Translated and updated, R
for Statistics includes a number of expanded and additional worked
examples.
Organized into two sections, the book focuses first on the R
software, then on the implementation of traditional statistical
methods with R.
Focusing on the R software, the first section covers:
- Basic elements of the R software and data processing
- Clear, concise visualization of results, using simple and
complex graphs
- Programming basics: pre-defined and user-created functions
The second section of the book presents R methods for a wide
range of traditional statistical data processing techniques,
including:
- Regression methods
- Analyses of variance and covariance
- Classification methods
- Exploratory multivariate analysis
- Clustering methods
- Hypothesis tests
After a short presentation of the method, the book explicitly
details the R command lines and gives commented results. Accessible
to novices and experts alike, R for Statistics is a clear and
enjoyable resource for any scientist.
Datasets and all the results described in this book are
available on the book s webpage at http:
//www.agrocampus-ouest.fr/math/RforStat
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